Machine Learning Science Graduate

Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success. 

Why Join Us?

To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win. 

In this role you will:

Travel is so much more than simply reaching your destination. Along the way you will make an immediate impact on reimagining the way people search for travel with our awesome team by inventing brand-new techniques to power global travel for everyone, everywhere. From building pipelines and prototyping new ML models with A/B testing, to applying new techniques to services that run tens of thousands of requests per second, there is no shortage of opportunities for technical innovation at Expedia Group – the sky’s the limit!

• Applying statistics methods like confidence intervals, point estimates and sample size estimates to make sound and confident inferences on data and A/B tests

• Applying Natural Language models to Google keyword analysis and applying meta models to our multi-objective ranking problem

• Communicating complex analytical topics in a clean & simple way to multiple partners and senior leadership (both internal & external)

• Conducting feature engineering and modifying existing models/techniques to suit business needs

• Developing domain expertise in fraud & risk to understand how to detect risky transactions

• Modeling rich and complex online travel data to understand, predict and optimize business metrics to help improve the traveler experience

• Framing business problems as data science problems with a concrete set of tasks

• Apply your domain (i.e. travel, online retail) knowledge, business acumen (understanding the underlying business objectives), and critical reasoning skills to your work

Minimum Requirements:

• Must be available to start on August 17, 2026

• Must be graduating between December 2025 and July 2026with a PhD degree in a technical, or analytical-related, subject such as Computer Science (with focus in areas like Artificial Intelligence, Machine Learning, Natural Language Processing, Data Mining, Data Science), Mathematics, Physics, Statistics, Operations Research, Electrical & Computer Engineering

• Must bewilling to relocate to city of job location if outside commuting distance

Preferred Experience:

• Helpful to understand ML techniques like Regression, Naïve Bayes, Gradient Boosting, Random Forests, SVMs, Neural Networks, and NLP

• Helpful to haveexperience with programming, statistical, and querying languages like Python, R, SQL/Hive, Java 

• Helpful to understand distributed file systems, scalable datastores, distributed computing and related technologies (Spark, Hadoop, etc.); implementation experience of MapReduce techniques, in-memory data processing, etc. 

• Helpful to be familiar with cloud computing, AWS specifically, in a distributed computing context

• Helpful to be able to effectively communicate and engage with a variety of partners (e.g., internal, external, technical, non-technical people) 

What We Offer:

Successful candidates will receive a competitive compensation package including comprehensive benefits and other perks, some of which are included below:

• The total cash range for this position in San Jose, CA is $170,000. The total cash range for this position in Seattle, WA is $160,000. Employees in this role have the potential to increase their pay based on ongoing, demonstrated, and sustained performance in the role. Starting pay for this role will vary based on multiple factors, including location and degree level.

• Hybrid work policy 

• Travel discounts

• Medical, dental, and vision insurance options

• Travel and wellbeing reimbursement

• Restricted Stock Units

• Pet insurance and time for pet bereavement

Next Steps:

Apply now! Our dedicated early careers team will review your application and suitable applicants will be encouraged to complete an immersive strength based online assessment as the first step. Depending on the role profile you are applying to, selected candidates may also be asked to take a skills-based screening assessment.   

Candidates who are invited to a final round interview will have the opportunity to meet with members of our team through two virtual interviews covering both technical and behavioral skills related to the position. These interviews will also be a chance for you to learn more about us, too!